NLP & Language AI
Extract meaning from unstructured text.
Text classification, entity extraction, sentiment analysis, semantic search, and document understanding: at scale and in production.
Free, no commitment. Takes about 30 seconds.
What we build
NLP capabilities
Text classification
Categorize documents, tickets, reviews, or messages by topic, intent, or priority. Multi-label and multi-class.
Entity extraction
Extract named entities, dates, amounts, locations, and custom domain entities from unstructured text.
Sentiment analysis
Measure sentiment at document, sentence, and aspect levels. Works on reviews, support tickets, and social data.
Semantic search
Vector-based search that finds conceptually similar documents, not just keyword matches. Built on embedding models.
Document summarization
Extractive and abstractive summarization of long documents. Useful for contracts, reports, and research papers.
Document Q&A
RAG pipelines that let users ask questions against a private document corpus. Grounded answers with source citations.
Stack
NLP tools and models we use
Process
From raw text to production NLP
step 01
Text data audit
We assess your text corpus: volume, languages, quality, and domain specificity. We identify labeling requirements.
step 02
Model selection and fine-tuning
We choose between fine-tuning a pre-trained model vs. few-shot prompting based on your data size and latency requirements.
step 03
Evaluation pipeline
We build evaluation datasets and metrics beyond accuracy: F1, precision-recall curves, and qualitative spot-checks.
step 04
Serve and monitor
Production API with latency optimization, caching, and monitoring for distribution shift in input text.
Before you decide
The doubts everyone has before hiring us.
And what we do about each one.
AI projects never make it past the prototype.
Your data is assessed in the first week, and you get an honest answer on whether there is enough signal to build something useful.
Data assessment in week oneThis will just be a chatbot on top of an API.
Language models are used when they fit, like text and language tasks.
The right tool for the problemOur data is too sensitive to leave our infrastructure.
Model training can run entirely in your cloud, so your data never leaves your infrastructure.
We'll end up locked in to you.
Trained weights, training code, data pipelines and all documentation transfer to you on delivery.
Models and code are yours
FAQ
Common questions
Start understanding your text
Tell us what's buried in your documents.
What happens next
- 1
You tell us what you need. It takes about 2 minutes.
- 2
A real person replies within 4 business hours.
- 3
A 30-minute call to understand the project and agree on next steps.